3 citations · 4 across the 6 of their papers we have counts for
6 papers
Towards A Unified PAC-Bayesian Framework for Norm-based Generalization Bounds
Xinping Yi, Gaojie Jin, Xiaowei Huang +1
Understanding the generalization behavior of deep neural networks remains a fundamental challenge in modern statistical learning theory. Among existing approaches, PAC-Bayesian nor…
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent
Linfeng He, Yiming Sun, Sihao Wu +2
In this paper, we propose a novel framework for enhancing visual comprehension in autonomous driving systems by integrating visual language models (VLMs) with additional visual per…
Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving
Sihao Wu, Jiaxu Liu, Xiangyu Yin +5
The integration of Large Language Models (LLMs) into autonomous driving systems demonstrates strong common sense and reasoning abilities, effectively addressing the pitfalls of pur…
Tiny Refinements Elicit Resilience: Toward Efficient Prefix-Model Against LLM Red-Teaming
Jiaxu Liu, Xiangyu Yin, Sihao Wu +4
With the proliferation of red-teaming strategies for Large Language Models (LLMs), the deficiency in the literature about improving the safety and robustness of LLM defense strateg…
Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE
Jiaxu Liu, Xinping Yi, Sihao Wu +4
While Hyperbolic Graph Neural Network (HGNN) has recently emerged as a powerful tool dealing with hierarchical graph data, the limitations of scalability and efficiency hinder itse…
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks
Jiaxu Liu, Xinping Yi, Xiaowei Huang
Hyperbolic graph convolutional networks (HGCNs) have demonstrated significant potential in extracting information from hierarchical graphs. However, existing HGCNs are limited to s…